Mitigation of GPS multipath error using recursive least squares adaptive filtering

Positional accuracy of GPS is limited by various error sources like ionosphere, troposphere, clock, instrumental bias, multipath etc. Among these, multipath errors are quite significant, since it should be dynamically modelled with respect to GPS receiver environment. In this paper, multipath error is estimated based on both code and carrier phase measurements using CMC (code minus carrier) method. It is verified with experimental static dual frequency GPS receiver data. The multipath time series data is applied to various Recursive Least Squares (RLS) adaptive filtering algorithms to minimize the multipath error. The results are encouraging and significant reduction of multipath error is observed. The convergence of RLS filters is faster than the conventional Least Mean Squares (LMS) adaptive filters. These RLS filters can also be applied to real time kinematic GPS applications.